Underwater manifold leakage accident comprehensive evaluation method fusing effect theory and risk matrix

Abstract

The invention discloses a comprehensive evaluation method for an underwater manifold leakage accident by fusing an effect theory and a risk matrix. Designing a risk attitude questionnaire, collecting expert suggestions, obtaining a utility value fuzzy evaluation table of different experts through trapezoidal binary semantics, and obtaining utility value trapezoidal binary semantics; aggregating different expert suggestions based on a utility value trapezoidal binary semantic aggregation operator, and performing defuzzification on an aggregation result to obtain trapezoidal binary semantic optimal single values of different expert utility values; fitting the optimal single value by adopting a polynomial function to obtain a comprehensive utility function reflecting the risk attitude of the expert group; grading the loss value and the occurrence probability of the risk accident, drawing a utility undifferentiated curve corresponding to each risk grade, and defining the risk grade and related parameters of a related region, thereby constructing a risk matrix; and in the constructed risk matrix, the occurrence possibility and severity parameters of the underwater manifold leakage accident are imported, the risk level of each node is determined, and corresponding control suggestions are given.

Description

Technical Field

[0001] The present invention belongs to the technical field of underwater pipeline network leakage accident prevention and control, and relates to a comprehensive evaluation method for underwater pipeline network leakage accidents integrating the fusion effect theory and the risk matrix. Background Art

[0002] The underwater pipeline network is an important part of the deep-water oil and gas production system. Its complex working environment and changing working conditions make the risk of leakage accidents remain high. Once a leakage accident occurs, it will not only cause serious damage to the marine ecological environment, but also lead to significant economic losses and social impacts. Therefore, how to scientifically and systematically conduct a comprehensive evaluation of the risks of underwater pipeline network leakage accidents has become a research hotspot and difficulty in the field of ocean engineering.

[0003] At present, the following two methods are mainly used for the risk assessment of underwater pipeline network leakage accidents: the risk matrix method based on qualitative analysis and the effect theory method based on quantitative models. The risk matrix method has the advantages of being intuitive and easy to operate, but the division of risk probability and loss value is relatively subjective, and it is difficult to fully reflect the actual situation. Especially in the fuzzy transition area between different risk levels, the evaluation results are not accurate enough; while the method based on the effect theory can quantify the risk attitude through the utility function, overcoming the problem of excessive subjectivity of the traditional risk matrix, but its construction process is complex and it is difficult to be directly applied to the comprehensive evaluation of multiple risk nodes.

[0004] In addition, in the existing technology, there are also certain limitations in the collection and processing of expert opinions. Traditional methods usually directly collect numerical opinions or fuzzy language evaluations, but do not fully consider the differences and fuzziness between expert opinions, which may lead to information loss or bias, thus affecting the objectivity and accuracy of risk assessment. Especially in the comprehensive risk assessment involving multiple disciplines and fields, how to efficiently aggregate and utilize expert opinions is still an urgent problem to be solved.

[0005] In summary, the existing risk assessment technologies face the following main problems in practical applications:

[0006] (1) The risk matrix method is highly subjective and fails to quantify the transitional characteristics in the risk level division;

[0007] (2) The effect theory method has a complex model and fails to intuitively reflect the distribution characteristics of risk levels;

[0008] (3) The expert opinion processing method has deficiencies and cannot fully excavate the effective information in the opinions.

[0009] Based on this, the present invention proposes a comprehensive evaluation method for underwater pipeline leakage accidents that combines the effect theory and the risk matrix. By introducing trapezoidal two-tuple semantics and the expected utility theory, the fuzzy processing of expert opinions is organically combined with the intuitive representation form of the risk matrix to achieve a scientific, quantitative, and comprehensive evaluation of underwater pipeline leakage accidents, thereby providing a more reliable decision-making basis for risk control. Summary of the Invention

[0010] The object of the present invention is to provide a comprehensive evaluation method for underwater pipeline leakage accidents that combines the effect theory and the risk matrix to solve the problems existing in the prior art.

[0011] The technical solution of the present invention:

[0012] A comprehensive evaluation method for underwater pipeline leakage accidents that combines the effect theory and the risk matrix, comprising the following steps:

[0013] Step 1: Design a risk attitude questionnaire to collect expert opinions. Through trapezoidal two-tuple semantics, a fuzzy evaluation table of utility values of different experts is summarized to obtain the trapezoidal two-tuple semantics of utility values.

[0014] Step 2: Based on the aggregation operator (TFTWG) of trapezoidal two-tuple semantics of utility values, the aggregation of different expert opinions is realized, and then the defuzzification of the aggregation result is carried out to obtain the best single value of the trapezoidal two-tuple semantics of different expert utility values.

[0015] Step 3: Use a polynomial function to fit the best single value to obtain a comprehensive utility function that can reflect the risk attitude of the expert group.

[0016] Step 4: According to relevant specifications or expert opinions, classify the risk loss value and risk occurrence probability of risk accidents, draw the utility indifference curves corresponding to each risk level, and define the risk levels and relevant parameters of relevant regions, thereby constructing a risk matrix.

[0017] Step 5: In the constructed risk matrix, import the occurrence possibility and severity parameters of underwater pipeline leakage accidents, determine the risk levels of each node, and give corresponding control opinions.

[0018] The present invention first investigates and collects the risk attitudes of the expert group members towards the underwater pipeline system through trapezoidal two-tuple semantics and converts them into a quantitative utility function model; then, constructs a utility indifference curve, introduces the expected utility theory, combines the utility function with the risk matrix, and constructs a mathematical model between the risk probability and loss value under different risk levels; finally, unifies the dimensions of the risk occurrence probability and loss value of each risk node, imports them into the risk matrix coordinate system, and conducts a comprehensive evaluation of underwater pipeline leakage accidents.

[0019] The beneficial effects of the present invention:

[0020] (1) By integrating the effect theory and the risk matrix, and introducing the utility function model on the basis of the traditional risk matrix, the present invention overcomes the problems of strong subjectivity in risk level division and insufficient handling of fuzzy transition regions in the prior art, and realizes the quantitative correlation between risk probability and loss value. The utility function model can more completely and scientifically express the changing trend of the risk attitude of the expert group, ensuring the scientificity of the results. Compared with the prior art, the present invention also overcomes the disadvantages of uneven risk level transition and excessive inflection points;

[0021] (2) The present invention uses trapezoidal two-tuple semantics and its aggregation operator (TFTWG) to investigate the risk attitude of experts, which can reduce the information loss generated in the quantitative conversion of expert semantics and improve the integrity of the collection of expert risk attitude information;

[0022] (3) The present invention constructs a risk matrix model based on the utility indifference curve, and intuitively presents the complex risk analysis results as a visual chart, which is convenient for risk managers to quickly identify the risk levels of each node, so as to make scientific control decisions. Description of the Drawings

[0023] Figure 1 is the flow chart of the comprehensive evaluation method for underwater pipeline leakage accidents provided by the present invention;

[0024] Figure 2 is the schematic diagram of the fitting result of the utility function provided by the present invention;

[0025] Figure 3 is the schematic diagram of the risk matrix combined with the utility theory provided by the present invention;

[0026] Figure 4 is the schematic diagram of the risk matrix analysis result provided by the present invention. Detailed Embodiments

[0027] The specific structure and implementation process of the present solution will be described in detail below through specific embodiments and drawings.

[0028] As Figure 1 shown, in an embodiment of the present invention, a comprehensive evaluation method for underwater pipeline leakage accidents integrating the effect theory and the risk matrix is disclosed, including the following steps:

[0029] Step 1: Design a risk attitude questionnaire, with the loss value l as the independent variable and the quantified utility value u(l) as the dependent variable. Among them, the loss value is represented by numbers, and the utility value is represented according to the trapezoidal two-tuple scale in Table 1. After collecting the questionnaires of each expert and summarizing them, a fuzzy evaluation table of the utility values of different experts is obtained.

[0030] Table 1 Trapezoidal two-tuple of utility values

[0031]

[0032] The trapezoidal two-tuple semantics can better retain the information of expert opinions. In order to accurately and completely express the attitude of experts towards the loss value, the present invention sets a 9-level utility value. Among them, U0 and U10 represent the upper and lower limits of the utility value interval. When the effect value is U0, it means that the system is in an ideal state and the economic loss value is 0. When the effect value is U10, it means that the system has reached the maximum loss value l max = 10000.

[0033] Step 2: Based on the trapezoidal two-tuple aggregation operator (TFTWG), the aggregation of different expert opinions is realized. The mathematical model of TFTWG is as follows:

[0034]

[0035] In the formula, represents the trapezoidal two-tuple semantic value evaluated by the i-th expert; n represents the number of experts; ω i represents the expert weight of the i-th expert; Δ and Δ -1 represent the generalized transformation function and the inverse transformation function in the two-tuple semantic theory respectively;

[0036] According to the defuzzification rule of the trapezoidal fuzzy number, the defuzzification is performed on the aggregation result of expert opinions obtained from the above formula to obtain the best single value of the trapezoidal two-tuple of different expert utility values.

[0037] Step 3: In order to retain the information of the comprehensive utility function as much as possible, a polynomial function is used to fit the best single value obtained in Step 2 to obtain a comprehensive utility function u(l) that can reflect the risk attitude of the expert group.

[0038] In order to retain the information of the comprehensive utility function as much as possible, a scatter plot is drawn in the loss-utility coordinate system, with the abscissa being the economic loss value and the ordinate being the effect value. A polynomial function is used to fit the best single value obtained in Step 2 to obtain a comprehensive utility function u(l) that can reflect the risk attitude of the expert group. l represents the loss value and is the independent variable; u represents the utility value and is the dependent variable; the three risk attitudes are risk aversion, risk opposition, and risk propensity attitudes, and the corresponding utility functions are described by logarithmic function, linear function, and exponential function respectively, as follows:

[0039]

[0040] Step 4: Construct a risk matrix to achieve a comprehensive evaluation of the underwater pipeline leak accident. To adapt to the actual situation of engineering applications, it is necessary to divide the risk levels according to relevant specifications or expert opinions. Determine the horizontal and vertical coordinate intervals of each level in the loss-probability coordinate system, draw the indifference curves of utility corresponding to each risk level, and define the risk levels and relevant parameters of the relevant regions.

[0041] Divide the risk loss value of the underwater pipeline leak into 5 levels and determine the boundary values of the 5 levels; similarly, divide the risk occurrence probability into 5 levels and formulate the division boundaries according to the specifications issued by the Norwegian Classification Society; take the risk loss value and the risk occurrence probability as the horizontal and vertical coordinates respectively to construct a risk matrix;

[0042] To achieve the aggregation of utility theory and the risk matrix, introduce the expected utility theory; regard the expected utility value composed of the risk occurrence probability and the loss value as the risk level, where the risk occurrence probability is obtained from historical accident statistical data; based on this, construct an indifference curve of utility to represent the comprehensive evaluation of the risk level of a certain point in the loss-probability coordinate system; each point on the same indifference curve of utility has the same expected utility value;

[0043] To construct the indifference curve of utility, determine the expected utility values of each risk level; assume that there is an initial reference point (l′, p′) in the risk matrix, and calculate any point (l, p) that has the same expected utility value as it; it can be solved by constructing an expected utility value equation, as shown in the following formula:

[0044] pu(l)+(1 - p)u(0) = p′u(l′)-(1 - p′)u(0)

[0045] In the formula, p represents the risk occurrence probability, l′, p′ represent the risk loss value and the risk occurrence probability of the initial reference point; u(0) represents the upper limit of the effect value interval. When u(0) = 0, there is pu(l) = p′u(l′); substitute the above equation into the comprehensive utility function u(l) obtained previously, that is, solve to obtain the mathematical model of the indifference curve of utility;

[0046] Construct a risk matrix to achieve a comprehensive evaluation of the underwater pipeline leak accident; to adapt to the actual situation of engineering applications, it is necessary to divide the risk levels according to relevant specifications or expert opinions; determine the horizontal and vertical coordinate intervals of each risk level in the loss-probability coordinate system, draw the indifference curves of utility corresponding to each risk level, and define the risk levels and relevant parameters of the relevant regions.

[0047] Step 5: Import the occurrence possibility and severity parameters of the underwater pipeline leak accident into the constructed risk matrix model, determine the risk levels of each node, and give corresponding control opinions.

[0048] First, integrate the risk attitudes of the expert group through a questionnaire survey to obtain the quantitative risk attitude trend of the expert group towards the underwater pipeline leakage accident. Then, determine the evaluation criteria for risk levels, the upper and lower limits of each level, the distribution of risk levels in the matrix, etc., so as to construct a risk matrix. Finally, analyze some risk nodes of the underwater pipeline leakage accident to obtain a comprehensive evaluation conclusion and put forward corresponding control opinions.

[0049] In this embodiment, first, integrate the risk attitudes of the expert group through a questionnaire survey to obtain the quantitative risk attitude trend of the expert group towards the underwater pipeline leakage accident. Then, determine the evaluation criteria for risk levels, the upper and lower limits of each level, the distribution of risk levels in the matrix, etc., so as to construct a risk matrix. Finally, analyze some risk nodes of the underwater pipeline leakage accident to obtain a comprehensive evaluation conclusion.

[0050] This embodiment has the following beneficial effects compared with the prior art:

[0051] (1) By integrating the effect theory and the risk matrix, and introducing the utility function model on the basis of the traditional risk matrix, the present invention overcomes the problems of strong subjectivity in risk level division and insufficient handling of fuzzy transition regions in the prior art, and realizes the quantitative correlation between risk probability and loss value. The utility function model can express the changing trend of the risk attitude of the expert group more completely and scientifically, ensuring the scientificity of the results. Compared with the prior art, the present invention also overcomes the disadvantages of uneven risk level transition and too many inflection points;

[0052] (2) The present invention uses trapezoidal two-tuple semantics and its aggregation operator (TFTWG) to investigate the risk attitudes of experts, which can reduce the information loss generated in the quantitative transformation of expert semantics and improve the integrity of the collection of expert risk attitude information;

[0053] (3) The present invention constructs a risk matrix model based on the utility indifference curve, and intuitively presents the complex risk analysis results as a visual chart, which is convenient for risk managers to quickly identify the risk levels of each node, so as to make scientific control decisions.

[0054] The following takes an underwater pipeline arranged in an oil and gas field in the South China Sea of China as an example, and combines the attached drawings to make a detailed description of the evaluation method of the present invention.

[0055] 1. To standardize the indicators, this embodiment uses monetary value to describe the loss value in the underwater pipeline leakage accident. Comprehensively consider various factors such as economy, manpower, and environment, and convert them into corresponding monetary values to describe the loss caused by the accident. During the evaluation process, 10% of the total cost of the underwater pipeline is selected as the maximum loss value l max . When the loss value is greater than l maxWhen the probability value p is any value, it is regarded as unacceptable. Therefore, the interval of the loss value l is set as [-l max ,0]. In this section, the total cost of the underwater pipeline system is set to 1 billion yuan, that is, l max = 100 million yuan.

[0056] 2. Take several independent variables l within the interval [-10000, 0], and invite five experts (E1, E2, E3, E4, and E5 respectively) to give corresponding utility value evaluations, so as to make the fitting result more in line with the risk attitude of the expert group. Then collect the results of the expert group and summarize them in Table 2.

[0057] The weights of the five experts are: 0.2694, 0.2155, 0.2458, 0.1340, and 0.1354 respectively. Then use the TFTWG operator to calculate the aggregated expert survey results to obtain the aggregated results in Table 2. Plot a scatter diagram in the loss-utility coordinate system and use a polynomial function for fitting to obtain the final utility function u(l), as shown in the following formula, and the function image is as Figure 2 shown.

[0058] u(l)= -1.117 + 2.647×10 -3 l + 3.8×10 -7 l 2 + 2.03×10 -11 l 3

[0059] Table 2 Survey results of the risk attitude of the expert group

[0060]

[0061] 3. The horizontal and vertical coordinates in the risk matrix represent the loss value and occurrence probability of the risk accident respectively. By consulting relevant materials and inviting members of the expert group to conduct risk assessment, the division rules of the risk level are determined, and the following important parameters are determined:

[0062] (1) Initial reference points for each risk level

[0063] According to the expected utility value theory, select the initial reference point under specific conditions, and require the risk probability value of the initial reference point to be 1. Therefore, only the loss value of the initial reference point corresponding to the risk level needs to be determined. Generally, the risk level is divided into 3-6 levels, and this embodiment is divided into 5 levels of risk. As shown in Table 3.

[0064] Table 3 Loss value of the initial reference point

[0065]

[0066] (2) Loss level boundary values

[0067] The meaning of this parameter is the boundary value corresponding to each loss value level in the risk matrix. The loss values of the underwater pipeline leakage accident are divided into 5 levels, and the boundary values of the 5 levels are given respectively, as shown in Table 4.

[0068] Table 4 Boundary Values of Loss Levels

[0069]

[0070] (3) Boundary Values of Probability Levels

[0071] The risk probability is an important parameter in the comprehensive evaluation of the underwater pipeline leakage accident. In this embodiment, the specification promulgated by the Norwegian Classification Society is selected as the basis to formulate the classification principle of the risk probability level. Since the change of the risk probability with the level in the specification is not a linear growth and cannot be directly used for the construction of the risk matrix, logarithmic normalization is performed on it.

[0072] 5. By using the formula pu(l)+(1 - p)u(0) = p′u(l′)-(1 - p′)u(0) and the initial reference point loss values in Table 4, the utility indifference curve functions corresponding to each risk level can be calculated and summarized as shown in the following formula:

[0073]

[0074] The above formula represents the utility indifference curve function in the 5 - order risk matrix. Since both the risk probability and the loss value are bounded, the interval of the risk probability is p ∈ [0, 1], and the loss value interval is [-l max , 0]. Therefore, the risk matrix can be divided into five parts by four function curves, which are five risk levels.

[0075] In the traditional risk matrix, the evaluation of the risk level generally adopts the method of multiplication. The risk level is regarded as the product of the probability and the loss, and the level is divided. Therefore, in the traditional risk matrix, risk iso - lines are often used to assist the analysis. The so - called risk iso - lines are a group of inverse proportional function lines. The product of the risk probability and the loss value of all points on the risk iso - line is equal, so they must be in the same risk level. However, this method ignores the influence of the expert's risk attitude and cannot comprehensively reflect the risk situation of the system. Therefore, the present invention introduces the utility indifference curve to replace the risk iso - line and divides the risk matrix into 5 levels, as Figure 3 shown. In Figure 3 , in order to more intuitively reflect the distribution of the risk levels, logarithmic processing is performed on the horizontal and vertical coordinates.

[0076] 5. The present invention quantifies the severity level according to the boundary values of the loss value levels in Table 4, and converts the 5 levels of severity into loss values applicable to the risk matrix. The conversion standard is shown in Table 5:

[0077] Table 5 Severity Level Conversion Criteria

[0078]

[0079] Process the prior probabilities and severity level results of the main risk sources of the underwater pipeline leakage accidents obtained by collection. Logarithmically normalize the prior probability values, convert the qualitative severity levels into quantitative loss values, then perform logarithmic processing, and mark them in Figure 4 to obtain the evaluation results in Table 6.

[0080] Table 6 Calculation Results of Some Risk Nodes

[0081]

[0082] Since the present invention can integrate the risk attitudes of the expert group, as can be seen from the utility function u(l), the overall utility function model after aggregating the expert opinions presents a convex shape, which indicates that the risk attitudes of the expert group members are risk-prone. The comprehensive evaluation results show that the overall risk level of the underwater pipeline leakage accidents and the main risk source levels are mostly in the third level, that is, within the controllable range, which is in line with the actual engineering situation.

[0083] At this point, those skilled in the art should recognize that although multiple exemplary embodiments of the present invention have been shown and described in detail herein, many other variations or modifications that conform to the principles of the present invention can still be directly determined or derived from the content disclosed in the present invention without departing from the spirit and scope of the present invention. Therefore, the scope of the present invention should be understood and determined to cover all these other variations or modifications.

Claims

1. A comprehensive evaluation method for underwater manifold leakage accidents integrating effect theory and risk matrix, characterized in that: The steps include: Step 1: Design a risk attitude questionnaire, collect expert opinions, and summarize the utility value fuzzy evaluation table of different experts through trapezoidal binary semantics to obtain the utility value trapezoidal binary semantics; Step 2: Based on the aggregation operator of utility value trapezoidal binary semantics, the opinions of different experts are aggregated, and then the aggregation results are defuzzified to obtain the optimal single value of trapezoidal binary semantics of different expert utility values; Step 3, use a polynomial function to fit the best single value to obtain a comprehensive utility function that can reflect the risk attitude of the expert group; Step 4: According to relevant specifications or expert opinions, the risk loss value and risk probability of risk accidents are classified into different levels, the utility indifference curves corresponding to each risk level are drawn, and the risk level and related parameters of the relevant areas are defined, so as to construct a risk matrix; Step 5: In the constructed risk matrix, import the possibility and severity parameters of underwater manifold leakage accidents, determine the risk level of each node, and give corresponding management and control opinions.

2. The comprehensive evaluation method for underwater manifold leakage accident according to claim 1 is characterized in that: The specific implementation process of step 1 is as follows: Utility Value Ladder Binary Semantics Among them, U0 and U10 represent the upper and lower limits of the utility value interval. When the effect value is U0, it means that the underwater manifold system is in an ideal state and the economic loss value caused by the risk accident is 0; when the effect value is U10, it means that the underwater manifold system has reached the maximum loss value l max =10000.

3. The comprehensive evaluation method for underwater manifold leakage accident according to claim 1 is characterized in that: The specific implementation process of step 2 is as follows: Based on the trapezoidal binary semantics aggregation operator, the aggregation of different expert opinions is realized. The mathematical model of the aggregation operator is as follows: In the formula, represents the trapezoidal binary semantic value of the i-th expert evaluation; n represents the number of experts; ω i represents the expert weight of the i-th expert; Δ and Δ -1 They represent the generalized transformation function and the inverse transformation function in the binary semantic theory respectively; According to the defuzzification rules of trapezoidal fuzzy numbers, the expert opinion aggregation results obtained by the above formula are defuzzified to obtain the optimal single value of trapezoidal binary semantics with different expert utility values.

4. The comprehensive evaluation method for underwater manifold leakage accident according to claim 1 is characterized in that: The specific implementation process of step 3 is as follows: In order to retain the information of the comprehensive utility function as much as possible, a scatter plot is drawn in the loss-utility coordinate system, with the horizontal axis representing the economic loss value and the vertical axis representing the effect value. The best single value obtained in step 2 of the polynomial function fitting is used to obtain the comprehensive utility function u(l) that can reflect the risk attitude of the expert group. l represents the loss value, which is the independent variable; u represents the utility value, which is the dependent variable; the three risk attitudes are risk aversion, risk opposition, and risk tendency attitudes, and the corresponding utility functions are described by logarithmic function, linear function, and exponential function, respectively, as shown in the following formula:

5. The comprehensive evaluation method for underwater manifold leakage accident according to claim 1 is characterized in that: The specific implementation process of step 4 is as follows: The risk loss value of underwater manifold leakage is divided into 5 levels, and the boundary values ​​of the 5 levels are determined; the risk probability is also divided into 5 levels, and the division boundaries are formulated according to the specifications issued by the Norwegian Classification Society; the risk loss value and the risk probability are used as the horizontal and vertical coordinates respectively to construct a risk matrix; In order to realize the convergence of utility theory and risk matrix, the expected utility theory is introduced; The expected utility value composed of the risk probability and the loss value is regarded as the risk level, where the risk probability is obtained from historical accident statistics. Based on this, a utility indifference curve is constructed to represent the comprehensive evaluation of the risk level of a certain point in the loss-probability coordinate system. Each point on the same utility indifference curve has the same expected utility value. In order to construct the utility indifference curve, the expected utility value of each risk level is determined; assuming that there is an initial reference point (l′, p′) in the risk matrix, calculate any point (l, p) with the same expected utility value; the expected utility value equation can be constructed to solve it, as shown in the following formula: pu(l)+(1-p)u(0)=p′u(l′)-(1-p′)u(0) In the formula, p represents the probability of risk occurrence, l′, p′ represent the risk loss value and the probability of risk occurrence of the initial reference point; u(0) represents the upper limit of the effect value interval, when u(0) = 0, there exists pu(l) = p′u(l′); Substitute the above equation into the comprehensive utility function u(l) obtained in the previous article, that is, solve and obtain the mathematical model of the utility indifference curve; Construct a risk matrix to achieve a comprehensive evaluation of underwater manifold leakage accidents; in order to adapt to the actual scenario of engineering applications, it is necessary to divide the risk levels according to relevant specifications or expert opinions; determine the horizontal and vertical coordinate intervals of each risk level in the loss-probability coordinate system, draw the utility indifference curves corresponding to each risk level, and define the risk level and related parameters of the relevant area.

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